Bipartisan Legislation Tackles Healthcare Identification Crisis
Representatives Mike Kelly (R-PA) and Bill Foster (D-IL) have reintroduced the Patient Matching and Transparency in Certified Health IT (MATCH IT) Act of 2025. The bipartisan bill, cosponsored by Rep. Seth Moulton (D-MA), builds upon previous efforts to address one of healthcare’s most persistent challenges: patient misidentification across disparate systems.
This renewed legislation targets a fundamental gap in healthcare interoperability by establishing an industry standard definition for “patient match rate.” This standardized metric would allow consistent measurement of patient matching accuracy throughout the healthcare ecosystem, creating accountability and transparency where little currently exists.
Beyond measurement, the MATCH IT Act also aims to improve standardization of patient demographic data elements across certified health IT products. This standardization would significantly enhance the ability to accurately match patients with their correct medical information across different healthcare organizations and systems.
Patient Safety Risks and Financial Impact
The consequences of patient misidentification extend far beyond administrative inconvenience. Clinicians unable to ensure accurate patient matching with electronic health record (EHR) data have encountered serious medical errors that, in some cases, have led to patient deaths.
To mitigate these risks, healthcare providers often resort to ordering duplicate tests to verify previous results, creating unnecessary costs and patient burden. Research indicates the financial impact is substantial, with some studies estimating the cost of duplicate medical records and mismatched data at approximately $1,950 per patient per inpatient stay.
The financial toll extends to insurance claim processing as well. According to Black Book Research, more than one-third of all claim denials stem from inaccurate patient matching. This translates to average losses of $2.5 million per hospital and a staggering $6.7 billion annually across the U.S. healthcare system.
Industry Support for Standardized Approach
The MATCH IT Act has gained endorsement from Patient ID Now, a coalition of healthcare organizations committed to advancing nationwide patient identification strategies. The coalition includes founding members such as the American Health Information Management Association (AHIMA), the College of Healthcare Information Management Executives (CHIME), HIMSS, and Intermountain Health.
“The American Health Information Management Association (AHIMA) commends Representatives Mike Kelly and Bill Foster for once again leading the charge to protect patient safety and improve patient matching,” said Maria Caban Alizondo, PhD, RHIT, FAHIMA, AHIMA president and board chair.
She further emphasized the legislation’s potential benefits: “The MATCH IT Act would decrease rates of patient misidentification, improve patient privacy and care and bring down costs within the healthcare ecosystem associated with mismatched patient records. AHIMA looks forward to the passage of this critical legislation.”
Path Forward for Healthcare Interoperability
As healthcare continues its digital transformation, accurate patient identification remains a cornerstone for quality care, patient safety, and operational efficiency. The MATCH IT Act represents a targeted approach to establishing the standards and measurements necessary for addressing this critical challenge.
By creating common definitions and standardizing demographic elements, the legislation aims to reduce the technical barriers that currently fragment patient information across healthcare systems. This standardization would benefit all stakeholders in the healthcare ecosystem—from patients receiving safer care to providers delivering more efficient services and insurers processing claims more accurately.
The reintroduction of this bipartisan legislation signals continued recognition of patient matching as a priority issue requiring federal attention and industry collaboration to resolve effectively.
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